This paper proposes a hybrid classiยฎcation learning system for databases that integrates rule induction and lazy learning. For rule induction learning, we use an entropy function based on Hellinger divergence to measure the amount of information each inductive rule contains. For lazy learning, we al
โฆ LIBER โฆ
A Multistrategy Approach to Classifier Learning from Time Series
โ Scribed by William H. Hsu; Sylvian R. Ray; David C. Wilkins
- Book ID
- 110253335
- Publisher
- Springer
- Year
- 2000
- Tongue
- English
- Weight
- 395 KB
- Volume
- 38
- Category
- Article
- ISSN
- 0885-6125
No coin nor oath required. For personal study only.
๐ SIMILAR VOLUMES
A multistrategy approach to classificati
โ
Chang-Hwan Lee; Dong-Guk Shin
๐
Article
๐
1999
๐
Elsevier Science
๐
English
โ 478 KB
Learning to Match the Schemas of Data So
โ
AnHai Doan; Pedro Domingos; Alon Halevy
๐
Article
๐
2003
๐
Springer
๐
English
โ 671 KB
Classifying Time Series Data: A Nonparam
โ
Juan Manuel Vilar; Josรฉ Antonio Vilar; Sonia Pรฉrtega
๐
Article
๐
2009
๐
Springer
๐
English
โ 692 KB
Meta-learning approaches to selecting ti
โ
Ricardo B.C. Prudรชncio; Teresa B. Ludermir
๐
Article
๐
2004
๐
Elsevier Science
๐
English
โ 244 KB
A hybrid approach to design efficient le
โ
Bikash Kanti Sarkar; Shib Sankar Sana
๐
Article
๐
2009
๐
Elsevier Science
๐
English
โ 461 KB
## a b s t r a c t Recently, use of a Learning Classifier System (LCS) has become promising method for performing classification tasks and data mining. For the task of classification, the quality of the rule set is usually evaluated as a whole rather than evaluating the quality of a single rule. Th
A semi-dependent decomposition approach
โ
J. Dรญez; J.J. del Coz; A. Bahamonde
๐
Article
๐
2010
๐
Elsevier Science
๐
English
โ 256 KB